| Echo state networks are universal L Grigoryeva, JP Ortega Neural Networks 108, 495-508, 2018 | 222 | 2018 |
| Approximation bounds for random neural networks and reservoir systems L Gonon, L Grigoryeva, JP Ortega The Annals of Applied Probability 33 (1), 28-69, 2023 | 70 | 2023 |
| Optimal nonlinear information processing capacity in delay-based reservoir computers L Grigoryeva, J Henriques, L Larger, JP Ortega Scientific reports 5 (1), 12858, 2015 | 53 | 2015 |
| Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems L Grigoryeva, JP Ortega Journal of Machine Learning Research 19, 1-40, 2018 | 52 | 2018 |
| Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality L Grigoryeva, J Henriques, L Larger, JP Ortega Neural Networks 55, 59-71, 2014 | 41 | 2014 |
| Risk bounds for reservoir computing L Gonon, L Grigoryeva, JP Ortega Journal of Machine Learning Research 21 (240), 1-61, 2020 | 39 | 2020 |
| Differentiable reservoir computing L Grigoryeva, JP Ortega Journal of Machine Learning Research 20 (179), 1-62, 2019 | 39 | 2019 |
| Discrete-time signatures and randomness in reservoir computing C Cuchiero, L Gonon, L Grigoryeva, JP Ortega, J Teichmann IEEE Transactions on Neural Networks and Learning Systems 33 (11), 6321-6330, 2021 | 37 | 2021 |
| Chaos on compact manifolds: Differentiable synchronizations beyond the Takens theorem L Grigoryeva, A Hart, JP Ortega Physical Review E 103 (6), 062204, 2021 | 29 | 2021 |
| Memory and forecasting capacities of nonlinear recurrent networks L Gonon, L Grigoryeva, JP Ortega Physica D: Nonlinear Phenomena 414, 132721, 2020 | 25 | 2020 |
| Estimation and empirical performance of non-scalar dynamic conditional correlation models L Bauwens, L Grigoryeva, JP Ortega Computational Statistics & Data Analysis 100, 17-36, 2016 | 25 | 2016 |
| Nonlinear memory capacity of parallel time-delay reservoir computers in the processing of multidimensional signals L Grigoryeva, J Henriques, L Larger, JP Ortega Neural computation 28 (7), 1411-1451, 2016 | 25 | 2016 |
| Learning strange attractors with reservoir systems L Grigoryeva, A Hart, JP Ortega Nonlinearity 36 (9), 4674, 2023 | 20 | 2023 |
| Expressive power of randomized signature C Cuchiero, L Gonon, L Grigoryeva, JP Ortega, J Teichmann The Symbiosis of Deep Learning and Differential Equations, 2021 | 16 | 2021 |
| Substitute or complement? Defining the relative place of EEG and fMRI in the detection of voluntary brain reactions D Gabriel, J Henriques, A Comte, L Grigoryeva, JP Ortega, E Cretin, ... Neuroscience 290, 435-444, 2015 | 16 | 2015 |
| Volatility forecasting using global stochastic financial trends extracted from non-synchronous data L Grigoryeva, JP Ortega, A Peresetsky Econometrics and Statistics, 2017 | 14 | 2017 |
| Protocol design challenges in the detection of awareness in aware subjects using EEG signals J Henriques, D Gabriel, L Grigoryeva, E Haffen, T Moulin, R Aubry, ... Clinical EEG and neuroscience 47 (4), 266-275, 2016 | 12 | 2016 |
| Dimension reduction in recurrent networks by canonicalization L Grigoryeva, JP Ortega Journal of Geometric Mechanics 13 (4), 647-677, 2021 | 11 | 2021 |
| Stability of Hamiltonian relative equilibria in symmetric magnetically confined rigid bodies L Grigoryeva, JP Ortega, S Zub arXiv preprint arXiv:1311.2256, 2013 | 9 | 2013 |
| Reservoir computing: information processing of stationary signals L Grigoryeva, J Henriques, JP Ortega Computational Science and Engineering (CSE) and IEEE Intl Conference on …, 2016 | 7 | 2016 |
Juan-Pablo OrtegaNanyang Technological UniversityVerified email at ntu.edu.sg
